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Longitudinal proteomic investigation of COVID-19 vaccination
Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated C...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501184/ https://www.ncbi.nlm.nih.gov/pubmed/36930526 http://dx.doi.org/10.1093/procel/pwad004 |
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author | Wang, Yingrui Zhu, Qianru Sun, Rui Yi, Xiao Huang, Lingling Hu, Yifan Ge, Weigang Gao, Huanhuan Ye, Xinfu Song, Yu Shao, Li Li, Yantao Li, Jie Guo, Tiannan Shi, Junping |
author_facet | Wang, Yingrui Zhu, Qianru Sun, Rui Yi, Xiao Huang, Lingling Hu, Yifan Ge, Weigang Gao, Huanhuan Ye, Xinfu Song, Yu Shao, Li Li, Yantao Li, Jie Guo, Tiannan Shi, Junping |
author_sort | Wang, Yingrui |
collection | PubMed |
description | Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac(®)) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins. We proposed two sets of potential biomarkers (seven from serum, five from PBMCs) at baseline using machine learning, and predicted the individual seropositivity 57 days after vaccination (AUC = 0.87). Based on the four PBMC’s potential biomarkers, we predicted the antibody persistence until 180 days after vaccination (AUC = 0.79). Our data highlighted characteristic hematological host responses, including altered lymphocyte migration regulation, neutrophil degranulation, and humoral immune response. This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after COVID-19 vaccination, shedding light on immunization mechanisms and individual booster shot planning. |
format | Online Article Text |
id | pubmed-10501184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-105011842023-09-15 Longitudinal proteomic investigation of COVID-19 vaccination Wang, Yingrui Zhu, Qianru Sun, Rui Yi, Xiao Huang, Lingling Hu, Yifan Ge, Weigang Gao, Huanhuan Ye, Xinfu Song, Yu Shao, Li Li, Yantao Li, Jie Guo, Tiannan Shi, Junping Protein Cell Research Articles Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac(®)) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins. We proposed two sets of potential biomarkers (seven from serum, five from PBMCs) at baseline using machine learning, and predicted the individual seropositivity 57 days after vaccination (AUC = 0.87). Based on the four PBMC’s potential biomarkers, we predicted the antibody persistence until 180 days after vaccination (AUC = 0.79). Our data highlighted characteristic hematological host responses, including altered lymphocyte migration regulation, neutrophil degranulation, and humoral immune response. This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after COVID-19 vaccination, shedding light on immunization mechanisms and individual booster shot planning. Oxford University Press 2023-02-06 /pmc/articles/PMC10501184/ /pubmed/36930526 http://dx.doi.org/10.1093/procel/pwad004 Text en ©The Author(s) 2023. Published by Oxford University Press on behalf of Higher Education Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Wang, Yingrui Zhu, Qianru Sun, Rui Yi, Xiao Huang, Lingling Hu, Yifan Ge, Weigang Gao, Huanhuan Ye, Xinfu Song, Yu Shao, Li Li, Yantao Li, Jie Guo, Tiannan Shi, Junping Longitudinal proteomic investigation of COVID-19 vaccination |
title | Longitudinal proteomic investigation of COVID-19 vaccination |
title_full | Longitudinal proteomic investigation of COVID-19 vaccination |
title_fullStr | Longitudinal proteomic investigation of COVID-19 vaccination |
title_full_unstemmed | Longitudinal proteomic investigation of COVID-19 vaccination |
title_short | Longitudinal proteomic investigation of COVID-19 vaccination |
title_sort | longitudinal proteomic investigation of covid-19 vaccination |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501184/ https://www.ncbi.nlm.nih.gov/pubmed/36930526 http://dx.doi.org/10.1093/procel/pwad004 |
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